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Record W1499848404 · doi:10.4212/cjhp.v60i5.209

Highlights of the 2006 CSHP Membership Survey

2007· article· en· W1499848404 on OpenAlexaffvenue
Carolyn Bornstein, Habibat Garuba

Bibliographic record

VenueThe Canadian Journal of Hospital Pharmacy · 2007
Typearticle
Languageen
FieldComputer Science
TopicOpen Source Software Innovations
Canadian institutionsUniversity of TorontoSouthlake Regional Health Center
Fundersnot available
KeywordsSurvey researchSurvey data collectionComputer-assisted web interviewingPolitical sciencePublic relationsBusinessBusiness administrationMarketingStatistics

Abstract

fetched live from OpenAlex

In June 2006, CSHP conducted an online survey of its members to obtain their input for the strategic planning process related to CSHP’s Vision 2010. The survey was designed to obtain feedback on the Society’s current services and the directions where CSHP should focus its efforts in the future. The survey, conducted through surveymonkey.com, consisted of 43 questions. An electronic invitation containing a link to the survey was sent to all CSHP members asking them to participate. Reminder emails were sent twice over a 4-week period. CSHP wants to share with its members what the survey revealed, so we have prepared this article to present some highlights of the survey results. A total of 543 CSHP members responded to the survey (22.4% of total membership at the time). However, not all questions were answered by all respondents.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.044
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.950
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.044
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.009
Science and technology studies0.0030.000
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0130.003

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.276
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2007
Admission routes2
Has abstractyes

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